A common approach to statistical modelling of extreme wind speeds is to use techniques from extreme value analysis, which use models built on asymptotic arguments to estimate probabilities of events beyond the range of the data. In meteorological applications, such probabilities are commonly used by practitioners to design infrastructure appropriately to defend against the natural hazard being studied. The most widely-used approach in extreme value analysis is to consider excesses above a suitably high threshold. Consider a sequence of independent and identically distributed (i.i.d.) random variables \(X_1, \hdots , X_n\) . Under weak conditions on the \(X_i\) , the unique, non-degenerate distribution that the scaled excesses of a threshold by \(X_i\)  converges to, as the threshold tends to the upper limit \(x_F\)  of \(X_i\) , is the generalised Pareto distribution (GPD) [1]}, [2]}. We make the assumption that this limiting result holds for a large enough threshold \(u\) . The GPD takes the form
\(\Pr (X_i-u > x | X_i > u) = {\left(1+\frac{\xi x}{\sigma _{u} }\right)}^{-1/\xi }_{+}, \mbox{ } x > 0\) 
